DAE-ConvBiLSTM: End-to-end learning single-lead electrocardiogram signal for heart abnormalities detection.
Bambang TutukoAnnisa DarmawahyuniSiti NurmainiAlexander Edo TondasMuhammad Naufal RachmatullahSamuel Benedict Putra TeguhFirdaus FirdausAde Iriani SapitriRossi PassarellaPublished in: PloS one (2022)
The development architecture for detecting heart abnormalities using an unsupervised learning DAE and supervised learning ConvBiLSTM can be proposed for an end-to-end learning algorithm. In the future, the precise accuracy of the ECG main waveform will affect heart abnormalities detection in clinical practice.